Early diagnosis is one of the primary determinants of mortality and morbidity from disease. The recognition of a variety of diseases, notably cancers, in apparently healthy subjects and subsequent treatment thereof is still problematic. Alterations in post-translational modifications of readily attainable samples from patients is the best indicator of the disease state, although most potential markers are as yet unknown. Current diagnostic tests are often inaccurate and invasive. For example in the case of the commonly used cancer marker prostate specific antigen, levels of normal expression vary dramatically between individuals, and current tests are only beginning to address this issue (See U.S. Pat. No. 6,261,791).
The covalent attachment of oligosaccharides to protein is the most common post-translational event and occurs in more than 50% of proteins, independent of membrane linkage. Glycosylation occurs at specific locations along the polypeptide backbone of the protein. There are usually two major types of glycosylation: glycosylation characterized by O-linked oligosaccharides, which are attached to serine or threonine residues; and glycosylation characterized by N-linked oligosaccharides, which are attached to asparagine residues in an Asn-X-Ser/Thr sequence, where X can be any amino acid except proline. N-acetylneuramic acid (also known as sialyl acid) is usually the terminal residue of both N-linked and O-linked oligosaccharides. Variables such as protein structure and cell type influence the number and nature of the carbohydrate units within the chains at different glycosylation sites. Glycosylation isomers are also common at the same site within a given cell type. The levels of glycosylation are a reflection of the levels and activities of different glycosyltransferases and glycosidases responsible for the intracellular construction of oligosaccharides.
There is now overwhelming evidence that glycosylation of glycoproteins is markedly altered in diseased cells (see for example Dwek et al., 2001; Hanisch, 2001; Hakomori, 2002). Altered glycosylation is a common feature in the transformation to malignancy of certain cancers and has been related to the invasiveness and metastatic potential of tumor cell lines. Studies have shown that variations in glycosylation have the potential to be used as diagnostic tools for disease states, in particular for cancers. Carbohydrate profiles of primary tumors have been correlated with tumor grade, metastatic potential, and disease prognosis (Litynska, et al., Melanoma Rsch., 2001, 205-212; Hakomori, S., 1989, Adv. Cancer Res., 52:257-331).
A number of studies have attempted to identify specific glycoproteins that are altered in disease states, in particular to recognize markers of cancer. In many of these studies, cell or tissue extracts were separated and probed using one or more lectins that were conjugated for visualization. The levels of binding of the lectin could thereafter be compared between tumor and control cells to identify protein bands with altered levels of glycosylation that could subsequently be excised for sequencing. However, traditional techniques for protein separation, such as 2D-electrophoresis are technically limiting in that only about 20% of the proteins loaded on a 2D-electrophoresis gel are visible, and of those, only the proteins with masses ranging between 10 kDa and 100 kDa are readily separated. In addition, relevant expression differences are difficult to confirm since multiple gels are difficult to prepare in a reproducible manner. Additional techniques to identify variations in glycosylations utilizing the affinity of glycoproteins to subsets of lectins include serial lectin-affinity chromatography (for example Endo, 1996, J. of Chromatography. A 720(1-2):251-61). Sequential chromatography steps using several lectins with different binding properties are used to purify a subset of glycoproteins. Subsequent identification techniques for either method usually involve proteolysis and mass spectroscopy. These methods are both time consuming and costly. Current techniques therefore can only detect a subset of available glycoproteins, have limited sensitivity to low levels of proteins, and are not quantitative. These methods also do not allow direct identification of glycosylated residues on specific molecules. Thus, there exists a need for convenient and efficient methods to analyze a large array of proteins and modifications thereof for the development of diagnostic devices.
Almost all glycoproteins exhibit polymorphism associated with their glycan moieties. This type of diversity is termed microheterogeneity and these different forms have been termed “glycoforms”. These variants were first characterized in the alpha1-acid glycoprotein (AAG) from human serum by Schmid et al (1962, Biochemistry J. 1:959). The microheterogeneity was found to be due to the occurrence of di-, tri-, and tetra-antennary glycans at the glycosylation sites. Much variability occurs in the regulation of later stage processing of N-linked glycosylations. N-linked glycosylation is initiated by the transfer of an oligosaccharide to asparagine residues of newly synthesized proteins. Subsequent modification of this oligosaccharide by Golgi enzymes (Hsieh, P., et al., 1983, J. Biol. Chem., 258:2555-2561) generates the extreme diversity of N-linked oligosaccharides found in mature glycoproteins. However, the regulation of these later stages of processing is only poorly understood. Microheterogeneity of oligosaccharide modifications is wide-spread and has been seen in a number of glycoproteins, including those found in disease states. For example, branching of N-linked oligosaccharides is increased in a number of differentiated and oncogenically transformed cells (Feizi, T., 1985, Nature, 314:53-57; Yamashita, K., et al., 1984, J. Biol. Chem., 259:10834-10840; Warren, L., et al., 1978, Biochem. Biophys. Acta., 516:97-127), as well as in metastases of murine melanomas and fibrosarcomas (Dennis, J. W., et al., 1987, Science, 236:582-585). This is likely to have physiologically significant consequences, since altered protein glycosylation can affect processes such as adhesion, metastasis and immune recognition. (Hubbard, S. C., 1987, Journal of Biological Chemistry, 262 (34):16403-16411). Because there is reason to believe that the variations of oligosaccharide modifications in disease states may correspond to distinct markers of disease on particular proteins of interest, a method that can easily identify and quantify this variability will provide a novel and valuable diagnostic tool.
Currently, most glycosylation sites are unknown and glycoprotein prediction is dependent on in silico prediction, rather than substantiated experimentation. In fact, more than 90% of glycosylation data in the C. elgans proteome database is based on in silico prediction (Hirabayashi, J., 2002, J. Chromatogr. B 771:67-87). Therefore, there exists a need for a method that could identify particular sites of oligosaccharide modification on individual proteins to provide valuable information to the research community.
Methods exist to purify separated carbohydrates, or separated glycoamino acids from glycoproteins to allow their identification (see for example U.S. Pat. No. 6,077,951). These methods can furnish useful information to allow identification of disease markers, however they are time consuming. To identify any particular glycosylation sites associated with an oligosaccharide moiety, multiple purification steps are required and these steps can limit the glycoproteins from which information could be gathered.
A more relevant method to identify glycosylation sites is disclosed in E.P. 1,008,852A1. This reference discloses a technique to identify specific glycoproteins using an immobilized binding agent which binds to either a sugar or a peptide sequence and a second, non-immobilized but easily identified binding partner which recognizes the other aspect of the glycoprotein (either the sugar or peptide). This technique, while a step forward in that it allows identification of modifications on specific proteins, is still limited in the detection levels that it allows. In addition, the analysis of multiple glycosylation sites or multiple peptides can become time consuming. A need clearly exists for more sensitive assays that can be used to identify modifications on proteins of interest and detect low levels of diagnostic analytes in solution
Building on the idea of analyzing proteins using multiple binding partners, E.P. 0,832,431B1 discloses a method to quantify proteins captured from solution using three binding agents: one to stabilize the protein and two to detect specific epitopes. In this reference oligonucleotides are linked to the specific recogntion agents and the binding of these molecules is recognized by amplification of the oligonucleotides (as described in U.S. 2002/0,051,974A1). In most cases these techniques are limited in that they only identify a particular epitope in a sample, they do not give structural information, nor do they differentiate between multiple forms of a target. Moreover, assays that use antibodies as capture agents have detection limits that are approximately 1% of the antibody Kd (1 picogram/ml for the highest affinity antibodies). The method described in E.P. 0,832,431B1 is clearly an improvement on previous techniques, in that it provides the possibility of detecting very small quantities of protein, however, it still requires additional washing steps, and because of the requirement for immobilizing an antigen, would only be useful for a restricted array of molecules since many may not bind properly. In addition, this method limits the possible analysis of post-translational modifications because the immobilization step can mask specific binding regions, in particular carbohydrate moieties. To overcome some of these difficulties, U.S. 2002/0,064,779A1 (also see Fredriksson et al., Nature Biotech. 20:473-477, 2002) discloses a method for identifying analytes in solution using a similar proximity based assay. This reference suggests that non-peptide modifications could be analyzed using this technique, however the method is not applied towards the detection of specific glycoproteins in solution, nor is it targeted towards classifying glycan heterogeneity in disease states.
Therefore, despite these advances, a need continues to exist for a method with improved sensitivity, improved range and requiring less manipulation to more rapidly analyze samples for the presence of and for the amount of target glycoproteins. There is additionally a need for an efficient method to discriminate the oligosaccharide modifications on proteins of interest from a population of proteins and to quantify said modifications, for the purpose of developing diagnostic tools to efficiently screen individuals for diseases such as cancer.